The biotechnology industry of 225 publicly held
companies provides the population of firms for this investigation
(Burrill & Lee, 1993). The sample from this population was
limited to firms which went public since 1982. Thus, the initial
sample was limited to 218 firms. These firms were then contacted
by phone with a request for a copy of the prospectus from their
IPO. A total of 106 companies were willing to provide a
prospectus representing a response rate of 48%. However, 15 of
these companies were excluded from the sample due to missing data
and 2 were excluded because warrants for shares in their parent
company were included in the IPO. Thus, our final sample
consisted of 89 firms.

To test for potential biases in this sample we
compared the average total assets and average total liabilities
of the firms in our sample in 1992 to the average total assets
and liabilities reported by Burill & Lee (1993) for all 225
public firms. Our sample averaged $11,123,000 in total assets and
$3,515,000 in total liabilities. Burill & Lee (1993) reported
the average total assets and total liabilities of the 225 public
biotechnology firms in 1992 as $11,377,000 and $3,313,000
respectively. In addition, the percentage of non-pharmaceutical
health care companies in our sample was 15% and the industry wide
percentage, as reported by Burill & Lee (1993) was 17%. Based
on these comparisons and the size of our sample, we believe we
have a fairly representative sample of the publicly held
biotechnology companies.

The data used in our analysis was gathered from
(1) the prospectus for each of the initial public offerings by
the firms in our sample, (2) Ernst and Young's industry annual
reports on the biotechnology industry and (3) the CRSP data
tapes.

Dependent Variable

Market Value Added. Market value added
is the difference between the company's market value at the time
of it's IPO and the capital employed by the company. MVA is a
cumulative measure of all of the stock market's assessment at a
particular time of the net present value of all a company's past
and planned capital projects (Stewart, 1991). It measures how
successful the company has been up to that time at investing
capital and how successful the market believes it is likely to be
in the future.

MVA is calculated from the difference between
two figures - an approximation of the fair market value of all
the companies debt and equity capitalization and capital employed
by the company. The market value is the actual market value of
the company's common equity plus the book value of preferred
stock, minority interests, long-term non-interest bearing
liabilities, all interest bearing liabilities and the present
value of all non-capitalized leases. The capital employed by the
company is essentially the company's assets less non-interest
bearing current liabilities plus certain equity equivalent
accounting reserves (Bad debt, LIFO, Goodwill amortization,
R&D, Unusual losses). In the case of biotechnology companies
the important adjustments are the addition of the accumulated
deficit during the startup phase, which we considered and unusual
loss, and depreciated R&D. These are both added into total
capital because in economic sense they represent investments by
the organization and therefore should be considered as part of
the capital employed by the firm.

The market value of the firm's common equity
was gathered from the CRSP data tapes at the end of the 1st day
of trading. The accounting information was gathered from the most
current financial statements included in the prospectus for the
initial public offering.

Independent Variables

Location. Based on the location of the
firm's headquarters, firms were coded into geographic territories
based on zip code and MSA (Metropolitan Statistical Areas). These
locations were then compared to the eight areas identified by
Burill & Lee as concentrations of biotechnology activity. In
order to capture the variance in the concentration of these eight
areas the location variable is the percentage of the nation's
total biotechnology firms located in the firm's specific MSA. A
"0" was recorded for firms not in one of the eight
geographical areas.

Citation Data. In this study we are
using citation analysis as an indication of the quality of the
scientific personnel of the biotechnology firm. The names of the
top scientists employed by each firm were gathered from the
prospectus of the firm's initial public offering. Only full time
employees were included in the list in order to control for
biases created by firms attempting to increase their
visibility/legitimacy by hiring a long list of scientific
advisors or consultants. Names of all scientific personnel listed
in the prospectus as well as top executives were compiled. We
then used the Science Citation Index to gather the total number
of citations for each scientist in the firm during his/her
career. These citations were then totaled to create a measure of
the quality of the scientific team employed by the biotechnology
firm.

Patents. From the offering firm's
prospectus, a count of the total number of patents held by that
firm was obtained. This includes both patents granted directly to
the firm and patents in which the firm is the sole licensee.

Rate of Product Development. In the
business section of each prospectus the companies report the
number of products under development or which have reached the
market. Only products which had reached the pre-clinical stage of
development or beyond were included. Multiple applications of the
same product were counted as a single product. The total number
of products was then divided by the age of the firm to create a
measure of the firm's rate of new product development.

Relative R&D Intensity. R&D
intensity was measured as the total R&D expenditures reported
by the firm in the prior year divided by the total expenditures
of the firm. The traditional measure of R&D intensity has
been R&D as a percentage of sales, but given their early
development stage most of these companies have little or no
revenue, therefore dividing through by total expenditures was the
logical choice to measure the firm's focus on R&D.

Control Variables

Age. MVA is a cumulative measure of the
wealth created by the firm. Therefore, the age of the firm in
years was entered into the model as a control variable.

# Employees. To control for any possible
effects of size on a firm's ability to generate wealth we entered
the total number of employees into the model as a control. The
number of employees was chosen as the control for size because
total assets is being used in the calculation of the dependent
variable.

The data was analyzed using ordinary least
squares regression. Descriptive statistics of the variables are
presented in Table 1. The average MVA of the firms in our sample
was $65.7 million. The average firm developed 0.65 products per
year and had control of 3.35 patents. With respect to location,
the average firm was located in a metropolitan area with 7.4% of
the total national biotechnology firms. The average firm spent
60% of its money on R&D. The research of the key scientists
of the average firm had been cited 126 times. The average firm
was 5.5 years old and employed 66 people. The correlation matrix
is presented in Table 2.

TABLE 1
DESCRIPTIVE STATISTICS

Variable

Mean

Standard Deviation

Market Value
Added

65,688,602

48,556,612

Location

7.37

5.31

Firm
Citations

125.64

134.81

Patents

3.35

4.88

Rate of New
Product Development

0.649

0.804

R&D
Intensity

0.598

0.229

Age

5.52

4.099

# Employees

66.52

72.76

TABLE 2
CORRELATION MATRIX

Variable

1

2

3

4

5

6

7

8

1. MVA

1.00

0.341

0.430

-0.013

0.354

0.421

0.152

0.066

2. Location

0.341

1.00

0.134

0.004

0.172

0.200

0.106

0.133

3. Citations

0.430

0.134

1.00

0.070

0.219

0.256

0.188

0.001

4. Patents

-0.013

0.004

0.070

1.00

0.183

0.096

0.183

0.039

5. Rate of
New Product Development

0.354

0.172

0.219

0.183

1.00

0.359

-0.082

0.036

6. R&D
Intensity

0.421

0.200

0.256

0.096

0.359

1.00

0.084

-0.177

7. Age

0.152

0.106

0.188

0.183

-0.082

0.084

1.00

0.008

8.Employees

0.066

0.133

0.001

0.039

0.036

-0.177

0.008

1.00

n = 89

Table 3 presents the results of the regression
analysis with MVA as the dependent variable. The adjusted R2 for
the model is 0.334. The F-statistic is 7.30 and is significant
beyond the 0.0001 level. These results indicate that the model is
explaining a significant amount of the variation in the MVA and
that the model is a good fit for the data.

The geographic concentration variable was
significantly positively related to MVA at the 0.05 level. These
results provide support for Hypothesis #1. Firms which are
located in a cluster of firms appear to create significantly more
shareholder wealth.

The firm citation measure was significantly
positively related to MVA at the 0.01 level. These results
provide strong support for Hypothesis #2. A strong research team,
as measured by the citation of their previous works, creates
significantly more wealth.

The number of patents controlled by the firm
was not significantly related to MVA. No support was found for
Hypothesis #3.

The rate of new product development was
positively related to MVA at the 0.05 level. These results
provide support for Hypothesis #4. Firm's which have a higher
rate of new product development appear to create significantly
more wealth.

The measure of relative R&D intensity was
significantly positively related to MVA at the 0.01 level. These
results provide strong support for Hypothesis #5. Firm's which
pursue a strategy of intense R&D investments create
significantly more wealth.